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The international development and social impact evidence community is divided about the use of machine-centered approaches in carrying out systematic reviews and maps. While some researchers argue that machine-centered approaches such as machine learning, artificial intelligence, text mining, automated semantic analysis, and translation bots are superior to human-centered ones, others claim the opposite. We argue that a hybrid approach combining machine and human-centered elements can have higher effectiveness, efficiency, and societal relevance than either approach can achieve alone. We present how combining lexical databases with dictionaries from crowdsourced literature, using full texts instead of titles, abstracts, and keywords. Using metadata sets can significantly improve the current practices of systematic reviews and maps. Since the use of machine-centered approaches in forestry and forestry-related reviews and maps are rare, the gains in effectiveness, efficiency, and relevance can be very high for the evidence base in forestry. We also argue that the benefits from our hybrid approach will increase in time as digital literacy and better ontologies improve globally.
Murat Sartas; Sarah Cummings; Alessandra Garbero; Akmal Akramkhanov. A Human Machine Hybrid Approach for Systematic Reviews and Maps in International Development and Social Impact Sectors. Forests 2021, 12, 1027 .
AMA StyleMurat Sartas, Sarah Cummings, Alessandra Garbero, Akmal Akramkhanov. A Human Machine Hybrid Approach for Systematic Reviews and Maps in International Development and Social Impact Sectors. Forests. 2021; 12 (8):1027.
Chicago/Turabian StyleMurat Sartas; Sarah Cummings; Alessandra Garbero; Akmal Akramkhanov. 2021. "A Human Machine Hybrid Approach for Systematic Reviews and Maps in International Development and Social Impact Sectors." Forests 12, no. 8: 1027.
Farmers face increased risks and vulnerability to the effects of climate change and land degradation on crop production due to the lack of information and impact assessment. This is especially true in the Khorezm, an irrigated agricultural region near the Aral Sea Basin (Uzbekistan) which represents eight million of irrigated land in Central Asia. Water scarcity requires research and introduction of alternative crops into a common winter wheat–cotton rotation. Mung bean (Vigna radiata) is considered as a drought-tolerant crop that could be implemented in Khorezm and other similar drought prone areas. The main objective of this study was modeling the triple rotation sequenced the winter wheat (WW), summer mung bean (MB) and cotton (C) as a single cropping system. Specific objectives were to (1) update the parameterization of the irrigated winter wheat and cotton modules in CropSyst to identify the key variables impacting the triple rotation (WW–MB–C) on overall crop yield; (2) to parameterize and validate the developed (CropSyst-based) model using controlled triple rotation data and (3) carry out scenario analyses to capture the influence of soil fertility levels and irrigation water shortage on crops growth, development and yields. The results revealed, for the first time, the impact of different soil-ecological factors such as high soil fertility (HSF) and low soil fertility (LSF) varying levels of irrigation water availability on crops in the triple crop rotation. Compared to LSF simulated yields of winter wheat and cotton under HSF were increased with 0.58 Mg ha−1 for WW grain and 0.21 Mg ha−1 for cotton while mung bean grain yields were not affected by different soil fertility levels. Scenario analyses showed the possibility of reduced (by 20%) irrigation for triple crop without the effect on yield. However, compared to full irrigation scenario, reduction of irrigation for 40 and 60% could decrease the rotation crops yields up to 33% and 40%, respectively. The developed model could be useful to increase the understanding of the nexus of food, energy and water in Khorezm and comparable regions of Central Asia, and to inform decision-making about sustainable use of available water resources.
Nazar Ibragimov; Yulduzoy Djumaniyazova; Jamila Khaitbaeva; Shirin Babadjanova; Jumanazar Ruzimov; Akmal Akramkhanov; John Lamers. Simulating Crop Productivity in a Triple Rotation in the Semi-arid Area of the Aral Sea Basin. International Journal of Plant Production 2019, 14, 273 -285.
AMA StyleNazar Ibragimov, Yulduzoy Djumaniyazova, Jamila Khaitbaeva, Shirin Babadjanova, Jumanazar Ruzimov, Akmal Akramkhanov, John Lamers. Simulating Crop Productivity in a Triple Rotation in the Semi-arid Area of the Aral Sea Basin. International Journal of Plant Production. 2019; 14 (2):273-285.
Chicago/Turabian StyleNazar Ibragimov; Yulduzoy Djumaniyazova; Jamila Khaitbaeva; Shirin Babadjanova; Jumanazar Ruzimov; Akmal Akramkhanov; John Lamers. 2019. "Simulating Crop Productivity in a Triple Rotation in the Semi-arid Area of the Aral Sea Basin." International Journal of Plant Production 14, no. 2: 273-285.
Accurate information of soil salinity levels enables for remediation actions in long-term operating irrigation systems with malfunctioning drainage and shallow groundwater (GW), as they are widespread throughout the Aral Sea Basin (ASB). Multi-temporal Landsat 5 data combined with GW levels and potentials, elevation and relative topographic position, and soil (clay content) parameters, were used for modelling bulk electromagnetic induction (EMI) at the end of the irrigation season. Random forest (RF) regressionwas applied to predict in situ observations of 2008–2011 which originated from a cotton research station in Uzbekistan. Validation, i.e. median statistics from 100 RF runs with a holdout of each 20% of the samples, revealed that mono-temporal (R2: 0.1–0.18, RMSE: 16.7–24.9 mSm−1) underperformed multi-temporal RS data (R2: 0.29–0.45; RMSE: 15.1–20.9 mSm−1). Combinations of multi-temporal RS data with environmental parameters achieved highest accuracies (R2: 0.36–0.50, RMSE: 13.2–19.9 mSm−1). Beside RS data recorded at the initial peaks of the major irrigation phases, terrain and GW parameters turned out to be important variables for the model. RF preferred neither raw data nor spectral indices known to be suitable for detecting soil salinity. Unexplained variance components result from missing environmental variables, but also from processes not considered in the data. A calibration of the EMI for electrical conductivity and the standard soil salinity classification returned an overall accuracy of 76–83% for the period 2008–2011. The presented indirect approach together with the in situ calibration of the EMI data can support an accurate mapping of soil salinity at the end of the season, at least in the type of irrigation systems found in the ASB.
Murodjon Sultanov; Mirzakhayot Ibrakhimov; Akmal Akramkhanov; Christian Bauer; Christopher Conrad. Modelling End-of-Season Soil Salinity in Irrigated Agriculture Through Multi-temporal Optical Remote Sensing, Environmental Parameters, and In Situ Information. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 2018, 86, 221 -233.
AMA StyleMurodjon Sultanov, Mirzakhayot Ibrakhimov, Akmal Akramkhanov, Christian Bauer, Christopher Conrad. Modelling End-of-Season Soil Salinity in Irrigated Agriculture Through Multi-temporal Optical Remote Sensing, Environmental Parameters, and In Situ Information. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 2018; 86 (5-6):221-233.
Chicago/Turabian StyleMurodjon Sultanov; Mirzakhayot Ibrakhimov; Akmal Akramkhanov; Christian Bauer; Christopher Conrad. 2018. "Modelling End-of-Season Soil Salinity in Irrigated Agriculture Through Multi-temporal Optical Remote Sensing, Environmental Parameters, and In Situ Information." PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 86, no. 5-6: 221-233.
Addressing soil salinity in irrigated drylands is tightly linked with water and land management decisions thus requiring interdisciplinary engagement. The salinity mapping approaches in Central Asia are undertaken through field sampling and laboratory analysis, which is a time consuming process. As a consequence, salinity maps are not available on time to estimate water requirements to cope with varying levels of soil salinity. Reducing the time lag between assessment and delivery of such maps would enable authorities to determine in advance appropriate water volumes for leaching the salts before and during the growing season. Research initiated in Uzbekistan context explored transdisciplinary and participatory approach to innovation development with local stakeholders. As one of the innovations, an electromagnetic induction meter (EM), a tool for rapid salinity assessment, was chosen and jointly with local salinity mapping related institutions tested, validated, and local capacities for its use developed. This paper redraws this process of innovation-focused stakeholder interaction and transdisciplinary research and discusses it with reference to ongoing debates on participatory and/or transdisciplinary innovation research. The existence of strong path dependencies within implementation oriented organizations could be observed, meaning that the innovation demands many changes to the existing system. Furthermore, the encountered challenges of participatory, transdisciplinary research in the hierarchically shaped setting of post-soviet Uzbekistan are illustrated in selected qualitative field notes and assessed. For improved joint learning and research in a transdisciplinary team, feedback cycles of mutual learning and critical reflection of how to theoretically and practically work in a transdisciplinary manner turned out to be crucial and not to be underestimated.
Akmal Akramkhanov; Muhammad Mehmood Ul Hassan; Anna-Katharina Hornidge. Redrawing Soil Salinity Innovation-Focused Stakeholder Interaction for Sustainable Land Management in Khorezm Province, Uzbekistan. Water 2018, 10, 208 .
AMA StyleAkmal Akramkhanov, Muhammad Mehmood Ul Hassan, Anna-Katharina Hornidge. Redrawing Soil Salinity Innovation-Focused Stakeholder Interaction for Sustainable Land Management in Khorezm Province, Uzbekistan. Water. 2018; 10 (2):208.
Chicago/Turabian StyleAkmal Akramkhanov; Muhammad Mehmood Ul Hassan; Anna-Katharina Hornidge. 2018. "Redrawing Soil Salinity Innovation-Focused Stakeholder Interaction for Sustainable Land Management in Khorezm Province, Uzbekistan." Water 10, no. 2: 208.
Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003–2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, “stratum-specific” classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate (p < 0.05) than a “global” classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation.
Fabian Löw; Alexander V. Prishchepov; François Waldner; Olena Dubovyk; Akmal Akramkhanov; Chandrashekhar Biradar; John P. A. Lamers. Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series. Remote Sensing 2018, 10, 159 .
AMA StyleFabian Löw, Alexander V. Prishchepov, François Waldner, Olena Dubovyk, Akmal Akramkhanov, Chandrashekhar Biradar, John P. A. Lamers. Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series. Remote Sensing. 2018; 10 (2):159.
Chicago/Turabian StyleFabian Löw; Alexander V. Prishchepov; François Waldner; Olena Dubovyk; Akmal Akramkhanov; Chandrashekhar Biradar; John P. A. Lamers. 2018. "Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series." Remote Sensing 10, no. 2: 159.
In the context of growing populations and limited resources, the sustainable intensification of agricultural production is of great importance to achieve food security. As the need to support management at a range of spatial scales grows, decision-support tools appear increasingly important to enable the timely and regular assessment of agricultural production over large areas and identify priorities for improving crop production in low-productivity regions. Understanding productivity patterns requires the timely provision of gapless, spatial information about agricultural productivity. In this study, dense 30-m time series covering the 2004–2014 period were generated from Landsat and MODerate-resolution Imaging Spectroradiometer (MODIS) satellite images over the irrigated cropped area of the Fergana Valley, Central Asia. A light-use efficiency model was combined with machine learning classifiers to assess the crop yield at the field level. The classification accuracy of land cover maps reached 91% on average. Crop yield and acreage estimates were in good agreement (R2 = 0.812 and 0.871, respectively) with reported yields and acreages at the district level. Several indicators of cropland intensity and productivity were derived on a per-field basis and used to highlight homogeneous regions in terms of productivity by means of clustering. Results underlined that regions with lower water-use efficiency were not only located further away from irrigation canals and intake points, but also had limited access to markets and roads. The results underline that yield could be increased by roughly 1.0 and 1.4 t/ha for cotton and wheat, respectively, if the access to water would be optimized in some of the regions. The minimum calibration requirement of the method and the fusion of multi-sensor data are keys to cope with the constraints of operational crop monitoring and guarantee a sustained and timely delivery of the agricultural indicators to the user community. The results of this study can form the baseline to support regional land- and water-resource management.
Fabian Löw; Chandrashekhar Biradar; Olena Dubovyk; Elisabeth Fliemann; Akmal Akramkhanov; Alejandra Narvaez Vallejo; Francois Waldner. Regional-scale monitoring of cropland intensity and productivity with multi-source satellite image time series. GIScience & Remote Sensing 2017, 55, 539 -567.
AMA StyleFabian Löw, Chandrashekhar Biradar, Olena Dubovyk, Elisabeth Fliemann, Akmal Akramkhanov, Alejandra Narvaez Vallejo, Francois Waldner. Regional-scale monitoring of cropland intensity and productivity with multi-source satellite image time series. GIScience & Remote Sensing. 2017; 55 (4):539-567.
Chicago/Turabian StyleFabian Löw; Chandrashekhar Biradar; Olena Dubovyk; Elisabeth Fliemann; Akmal Akramkhanov; Alejandra Narvaez Vallejo; Francois Waldner. 2017. "Regional-scale monitoring of cropland intensity and productivity with multi-source satellite image time series." GIScience & Remote Sensing 55, no. 4: 539-567.
This manuscript reviews scientific findings on agricultural systems, associated land degradation and selected remedies such as Conservation Agricultural (CA) practices to counterbalance these. In particular, this review addresses the research findings onCA practices conducted in the rainfed and irrigated systems in Central Asia. The arid and semi-arid croplands in this region are vulnerable to different types of soil and environmental degradation, and particularly to degradation caused by intensive tillage, irrigation water mismanagement, and cropping practices, especially in the Aral Sea Basin. Overall, the evidence shows that various CA elements, such as permanent beds, seems to be technically suitable for the major cropping systems and despite the heterogeneous conditions in the region. CA practices can contribute to combating on-going land degradation. No-till seeding along with the maintenance of a permanent soil coverage e.g. by residue retention, reduces wind and water erosion, increases water infiltration and storage which can reduce crop water stress, improve soil quality and increase soil organic matter. Further, CA practices can lead to similar or even higher crop yields while reducing production resource needs and costs considerably, including fuel, seeds, agrochemicals, water and labour. Nevertheless, the growing research evidence on the productivity, economic and environmental benefits that can be harnessed with CA, still is from a limited number of studies and hence more research at local scale is needed
A. Nurbekov; A. Akramkhanov; A. Kassam; D. Sydyk; Z. Ziyadaullaev; J.P.A. Lamers. Conservation Agriculture for combating land degradation in Central Asia: a synthesis. AIMS Agriculture and Food 2016, 1, 144 -156.
AMA StyleA. Nurbekov, A. Akramkhanov, A. Kassam, D. Sydyk, Z. Ziyadaullaev, J.P.A. Lamers. Conservation Agriculture for combating land degradation in Central Asia: a synthesis. AIMS Agriculture and Food. 2016; 1 (2):144-156.
Chicago/Turabian StyleA. Nurbekov; A. Akramkhanov; A. Kassam; D. Sydyk; Z. Ziyadaullaev; J.P.A. Lamers. 2016. "Conservation Agriculture for combating land degradation in Central Asia: a synthesis." AIMS Agriculture and Food 1, no. 2: 144-156.
Water scarcity and land degradation are among the most important factors affecting agricultural production and sustainability in the West Asia and North Africa (WANA) region and in Central Asia (CA). Various sustainable land management (SLM) technologies that help conserve and better use natural resources and hence improve the incomes and livelihoods of farmers are available and being adapted to these regions. However, to achieve better adoption by farmers and to ensure positive results from implementation, the SLM technologies in WANA and CA need to be disseminated on a large scale. Identifying the potential areas to target the implementation of selected SLM practices is necessary to help decision makers and facilitate the out-scaling process. With participation of specialists from the National Agriculture Research Systems, three agro-ecosystems, rangeland, irrigated, and rainfed, were defined for the WANA region, and the mountain agro-ecosystem was added for CA. Each agro-ecosystem was represented by a benchmark site where selected SLM technology was demonstrated. In WANA, these benchmark sites included the water harvesting Vallerani system (contour ridges and semicircular bunds) for rangeland, water-saving (raised-beds and deficit irrigation) for irrigated, and supplemental irrigation for rainfed agro-ecosystems. In CA, sites included pasture improvement for rangeland, raised-beds for irrigated, conservation agriculture for rainfed, and agro-forestry for mountain agro-ecosystems. The criteria used to identify potential areas for out-scaling consisted of land use, slope, water resources availability, precipitation, degree of land degradation, livestock density, soil depth, soil texture, and soil salinity. Global spatial datasets, such as the FAO Land Degradation Assessment in Drylands project (LADA), soil data from the Harmonized World Soil Database (HWSD), and soil depth from the Soil Map of the World were used to derive the required database. Available national data provided by the participating countries were used as supplemental sources. The derived maps were validated and verified by an interdisciplinary team of experts and researchers from the countries in both regions. Verification of the maps derived at regional level - using low resolution data, with more detailed data for some countries - indicated that potential areas for out-scaling SLM could be generally identified. However, for implementation purposes and to derive the extent of the potential areas, detailed data at national level is needed. Yet, the results are useful to guide decision makers to first identify the extent and distribution of the potential areas for each SLM and agro-ecosystem and, second, to prioritize the implementation. This will help in the out-scaling of SLM options to improve productivity and resilience.
Feras M Ziadat; Mira Haddad; Theib Oweis; Akmal Akramkhanov. Identification of potential areas for out-scaling sustainable land management options in West Asia, North Africa, and Central Asia. 2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics) 2015, 358 -363.
AMA StyleFeras M Ziadat, Mira Haddad, Theib Oweis, Akmal Akramkhanov. Identification of potential areas for out-scaling sustainable land management options in West Asia, North Africa, and Central Asia. 2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics). 2015; ():358-363.
Chicago/Turabian StyleFeras M Ziadat; Mira Haddad; Theib Oweis; Akmal Akramkhanov. 2015. "Identification of potential areas for out-scaling sustainable land management options in West Asia, North Africa, and Central Asia." 2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics) , no. : 358-363.
A. Akramkhanov; D.J. Brus; D.J.J. Walvoort. Geostatistical monitoring of soil salinity in Uzbekistan by repeated EMI surveys. Geoderma 2014, 213, 600 -607.
AMA StyleA. Akramkhanov, D.J. Brus, D.J.J. Walvoort. Geostatistical monitoring of soil salinity in Uzbekistan by repeated EMI surveys. Geoderma. 2014; 213 ():600-607.
Chicago/Turabian StyleA. Akramkhanov; D.J. Brus; D.J.J. Walvoort. 2014. "Geostatistical monitoring of soil salinity in Uzbekistan by repeated EMI surveys." Geoderma 213, no. : 600-607.
Rainfed and irrigated agricultural systems have supported livelihoods in the five Central Asian countries (CAC) for millennia, but concerns for sustainability and efficient use of land and water resources are long-standing. During the last 50 years, resource conserving technologies were introduced in large parts of the rainfed areas while the irrigated areas were expanded largely without considering resource conservation. In more recent years, the use of conservation agriculture (CA) practices has been reported for the different agricultural production (AP) zones in CAC, albeit centering on a single AP zone or on single factors such as crop yield, implements or selected soil properties. Moreover, conflicting information exists regarding whether the current practices that are referred to as ‘CA’ can indeed be defined as such. Overall information on an application of CA-based crop management in Central Asia is incomplete. This discussion paper evaluates experimental evidence on the performance of CA and other resource conserving technologies in the three main AP zones of CAC, provides an overview of farmer adoption of production practices related to CA, and outlines technical and non-technical challenges and opportunities for the future dissemination of CA practices in each zone. Agronomic (e.g. implements, crop yields, duration, and crop residues), institutional (e.g. land tenure) and economic (e.g. short vs. long-term profitability) perspectives are considered. At present, adoption of CA-based agronomic practices in the rainfed production zone is limited to partial crop residue retention on the soil surface or sporadically zero tillage for one crop out of the rotation, and hence the use of single CA components but not the full set of CA practices. In the irrigated AP zones, CA is not commonly practiced and many of the pre-conditions that typically encourage the rapid spread of CA practices appear to be absent or limiting. Further, our analysis suggests that given the diversity of institutional, socio-economic and agro-ecological contexts, a geographically differentiated approach to CA dissemination is required in the CAC. Immediate priorities should include a shift in research paradigms (e.g. towards more participatory approaches with farmers), development of commercially available reduced and no-till seeders suitable for smaller-scale farm enterprises, and advocacy so that decision makers understand how different policies may encourage or discourage innovations that lead towards more sustainable agricultural intensification in the CAC.
K.M. Kienzler; J.P.A. Lamers; A. McDonald; A. Mirzabaev; N. Ibragimov; Oybek Egamberdiev; E. Ruzibaev; Akmal Akramkhanov. Conservation agriculture in Central Asia—What do we know and where do we go from here? Field Crops Research 2012, 132, 95 -105.
AMA StyleK.M. Kienzler, J.P.A. Lamers, A. McDonald, A. Mirzabaev, N. Ibragimov, Oybek Egamberdiev, E. Ruzibaev, Akmal Akramkhanov. Conservation agriculture in Central Asia—What do we know and where do we go from here? Field Crops Research. 2012; 132 ():95-105.
Chicago/Turabian StyleK.M. Kienzler; J.P.A. Lamers; A. McDonald; A. Mirzabaev; N. Ibragimov; Oybek Egamberdiev; E. Ruzibaev; Akmal Akramkhanov. 2012. "Conservation agriculture in Central Asia—What do we know and where do we go from here?" Field Crops Research 132, no. : 95-105.
Akmal Akramkhanov; Ramazan Kuziev; Rolf Sommer; Christopher Martius; Oksana Forkutsa; Luiz Massucati. Soils and Soil Ecology in Khorezm. Cotton, Water, Salts and Soums 2011, 37 -58.
AMA StyleAkmal Akramkhanov, Ramazan Kuziev, Rolf Sommer, Christopher Martius, Oksana Forkutsa, Luiz Massucati. Soils and Soil Ecology in Khorezm. Cotton, Water, Salts and Soums. 2011; ():37-58.
Chicago/Turabian StyleAkmal Akramkhanov; Ramazan Kuziev; Rolf Sommer; Christopher Martius; Oksana Forkutsa; Luiz Massucati. 2011. "Soils and Soil Ecology in Khorezm." Cotton, Water, Salts and Soums , no. : 37-58.
Inefficient irrigation and the excessive use of water on agricultural land in the Aral Sea Basin over several decades have led to saline soils. The main objective of this paper is to identify the environmental predictors to model the spatial distribution of soil salinity in a highly irrigated landscape. Soil salinity at farm scale was measured in the topsoil (Total Dissolved Solids, TDS) and down to a depth of 1.5 m by electromagnetic conductivity meter (CMv) over a regular grid covering an area of approximately 15 km2 in Khorezm Province, Uzbekistan. Six nested samplings within selected grids were conducted to reveal short-distance variation. Apart from widely-used terrain indices and those acquired from remote sensing, data on distance to drainage channels and long-term average groundwater observations were used to account for local parameters possibly influencing soil salinity. Topsoil salinity (TDS) was seen to be highly variable even at short distances (40 m) compared to average bulk soil salinity (CMv). CMv readings were better correlated with factors obtained from remote sensing and distance to drains than TDS. This might be attributable to the fact that topsoil salts are dynamic in nature, and land management practices (e.g. leaching, cultivation, and irrigation) might have contributed considerably to spatial variation. The CMv shows the average amount of salt within a larger soil volume and to greater depth and is less affected by land management than topsoil salinity, which is reflected in the TDS. Most terrain indices showed a low correlation with topsoil and bulk salinity. There was a strong indication that the effects of water management are dominant and tend to outweigh the effects of environmental factors. The very low R2 for relationship of TDS with environmental factors is evidence that taking TDS samples close to the soil surface is not a good way to assess salinity trends in irrigated land. These findings have important implications for salinity survey methods on flat irrigated terrain: CMv seems to be a more reliable predictor than environmental proxy factors, even if the latter are easier to determine.
Akmal Akramkhanov; Christopher Martius; S.J. Park; J.M.H. Hendrickx. Environmental factors of spatial distribution of soil salinity on flat irrigated terrain. Geoderma 2011, 163, 55 -62.
AMA StyleAkmal Akramkhanov, Christopher Martius, S.J. Park, J.M.H. Hendrickx. Environmental factors of spatial distribution of soil salinity on flat irrigated terrain. Geoderma. 2011; 163 (1-2):55-62.
Chicago/Turabian StyleAkmal Akramkhanov; Christopher Martius; S.J. Park; J.M.H. Hendrickx. 2011. "Environmental factors of spatial distribution of soil salinity on flat irrigated terrain." Geoderma 163, no. 1-2: 55-62.
Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km2) results were used to upscale soil salinity to a district area (∼300 km2). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m−1). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70–90% of locations were correctly estimated.
Akmal Akramkhanov; Paul L. G. Vlek. The assessment of spatial distribution of soil salinity risk using neural network. Environmental Monitoring and Assessment 2011, 184, 2475 -2485.
AMA StyleAkmal Akramkhanov, Paul L. G. Vlek. The assessment of spatial distribution of soil salinity risk using neural network. Environmental Monitoring and Assessment. 2011; 184 (4):2475-2485.
Chicago/Turabian StyleAkmal Akramkhanov; Paul L. G. Vlek. 2011. "The assessment of spatial distribution of soil salinity risk using neural network." Environmental Monitoring and Assessment 184, no. 4: 2475-2485.
In Khorezm, a district of Uzbekistan situated in the Aral Sea Basin, soil salinization is an important driver of soil degradation in irrigated agriculture. The main objective of this study was to identify techniques that enable rapid estimation of soil salinity. Therefore, bulk electrical conductivity of the soil (ECa-meas) was measured with three different devices (2P, 4P, and CM-138) and electrical conductivity of the soil paste (ECp-meas) was measured with the so-called 2XP device. These measurements were compared with independent estimates of ECa-calc and ECp-calc based on laboratory measurements of the saturated extract, ECe, of soil samples from the same sites. Soil salinity could be assessed satisfactorily with all four devices. ECp-meas could be well reproduced by the 2XP device (R 2 = 0.76), whereas ECa-meas estimates using 2P, 4P, and CM-138 in the field were less accurate (R 2 < 0.50). The sensitivity of all devices to the main ions Cl− and Ca2 + suggests that the measuring principles are similar for all instruments. The devices can therefore be used interchangeably. Field assessment of soil salinity was considerably enhanced by the use of CM-138, because large areas can be quickly assessed, which may be desirable in spite of the lower accuracy.
Akmal Akramkhanov; R. Sommer; Christopher Martius; J. M. H. Hendrickx; P. L. G. Vlek. Comparison and sensitivity of measurement techniques for spatial distribution of soil salinity. Irrigation and Drainage Systems 2008, 22, 115 -126.
AMA StyleAkmal Akramkhanov, R. Sommer, Christopher Martius, J. M. H. Hendrickx, P. L. G. Vlek. Comparison and sensitivity of measurement techniques for spatial distribution of soil salinity. Irrigation and Drainage Systems. 2008; 22 (1):115-126.
Chicago/Turabian StyleAkmal Akramkhanov; R. Sommer; Christopher Martius; J. M. H. Hendrickx; P. L. G. Vlek. 2008. "Comparison and sensitivity of measurement techniques for spatial distribution of soil salinity." Irrigation and Drainage Systems 22, no. 1: 115-126.
Agricultural practices are believed to be the major anthropogenic source of enhanced nitrous oxide (N2O) gas emissions in New Zealand. Studies conducted in New Zealand generally suggest low N2O emission from pasture; however, there is little information for arable farming systems. This paper evaluates tillage and land use effects on N2O emissions using a closed chamber technique at an Ohakea silt loam (Gleyic luvisol) where winter oats (Avena sativa L.)/fodder maize (Zea mays L.) was double-cropped for 5 years. The tillage types included conventional tillage (CT) and no-tillage (NT) systems, and a permanent pasture (PP) was used as a control. Spatial variability in all treatments showed large inherent variations in N2O fluxes (a mean CV=119%), which reflected natural soil heterogeneity, and perhaps the measurement technique used rather than the real differences due to the tillage and cropping systems evaluated. On an annualised basis, N2O emissions measured from December 1998 to September 1999 from the PP (1.66 kg N2O-N/ha per year or 19 μg N2O-N/(m2 h)) were significantly lower than the CT and NT fields averaging at 9.20 (or 105) and 12.0 (or 137) kg N2O-N/ha per year (or μg N2O-N/(m2 h)), respectively. However, there were no differences in N2O emission rates between the CT and NT treatments. Seedbed preparation using a power harrow which followed within a few days of first ploughing the CT field reduced N2O emissions by 65% within the first hour after power harrowing. However, N2O emission rates returned to the pre-power harrowing levels at the next sampling period, which was 1 month later. There was a strong relationship between log-transformed data of soil water content (SWC) and N2O emissions in all treatments with r=0.73, 0.75 and 0.86 for the PP, CT and NT treatments, respectively. Seasonal variations in N2O emission from the PP were in the order of winter=autumn>summer. Although fluxes in the CT were higher in winter than in the autumn season, there were no differences between the summer and autumn data. The seasonal variations in N2O emission in the NT treatment were in the order of winter>autumn=summer.
M.A Choudhary; Akmal Akramkhanov; S Saggar. Nitrous oxide emissions from a New Zealand cropped soil: tillage effects, spatial and seasonal variability. Agriculture, Ecosystems & Environment 2002, 93, 33 -43.
AMA StyleM.A Choudhary, Akmal Akramkhanov, S Saggar. Nitrous oxide emissions from a New Zealand cropped soil: tillage effects, spatial and seasonal variability. Agriculture, Ecosystems & Environment. 2002; 93 (1):33-43.
Chicago/Turabian StyleM.A Choudhary; Akmal Akramkhanov; S Saggar. 2002. "Nitrous oxide emissions from a New Zealand cropped soil: tillage effects, spatial and seasonal variability." Agriculture, Ecosystems & Environment 93, no. 1: 33-43.